“Our research shows that 95% of businesses lack comprehensive AI governance frameworks, and only 5% can reliably measure bias and privacy risks in their models,” says Josefin Rosén, Trustworthy AI Specialist at SAS. “Trustworthy AI requires a governance-first approach, integrating oversight, compliance, and ethical standards at every stage of the AI lifecycle.”

Itumeleng Nomlomo, Senior Business Solutions Manager at SAS in South Africa, believes African BFSIs face unique challenges that include digital banking fraud.

SABRIC’s Annual Crime Statistics Report released last October highlighted that digital banking fraud surged by 45% and related financial losses rose by 47% in 2023.

“Financial institutions across the continent must modernise their decisioning processes and address gaps created by legacy systems. Unified platforms that integrate machine learning with decisioning models can reduce fraud risk while enhancing customer experience,” says Nomlomo.

Furthermore, SAS research titled Your journey to a GenAI future: A strategic path to success in banking reveals that 74% of banking leaders are concerned about protecting data privacy, and 71% cited security as a major challenge in AI adoption. Rosén says strong AI governance frameworks are vital for maintaining consumer trust, mitigate risks and support regulatory compliance.

“AI-powered fraud detection and personalised customer experiences will define the future of financial services,” says Rosén.

According to Nomlomo, BFSIs must leverage AI-driven analytics to anticipate customer needs and combat evolving financial crimes.

Both agree that increasing transparency in AI systems is essential for consumer trust.

“AI models must be explainable, and decisions should be auditable to ensure fairness and inclusivity,” says Rosén. “This is where SAS’s guiding principles for responsible innovation become key: human-centricity, transparency, accountability, privacy, inclusivity, and robustness.”

Furthermore, the role of continuous AI monitoring to maintain trust is important. Rosén believes it is important to use continuous monitoring to detect bias, privacy issues, model drift, and security vulnerabilities. The SAS research shows that 70% of companies fail to continuously monitor their GenAI systems.

“Integrating AI into customer decisioning can transform onboarding processes, reduce fraud, and personalise customer journeys for African BFSIs. However, this will only work if supported by robust data governance and model transparency. A proactive approach to AI literacy among senior leaders is essential to ensure responsible AI adoption and alignment with evolving customer expectations,” adds Nomlomo.

BFSIs must invest in comprehensive AI governance frameworks tailored to Africa’s regulatory and cultural landscape.

“AI trust is built through transparency, inclusive practices, and responsible innovation. Success lies not only in adopting advanced technologies but also in using them ethically and responsibly,” says Rosén.